Abstract Up to 80% of patients with Parkinson's disease (PD) will suffer from cognitive symptoms, including impaired attention, planning, reasoning and working memory as well as hallucinations, visuospatial dysfunction, and delusions. These impairments lead to mild cognitive impairment (PD-MCI) and dementia (PDD) in PD. Cognitive symptoms of PD are associated with enormous cost to our society. There are no clear biomarkers and few effective treatments for PD-MCI/PDD. Because risk for PD increases dramatically with age, this problem will surge as our population grows older. The mechanisms contributing to PD-MCI/PDD are unknown. Our group has found that low-frequency (1-8 Hz; or delta/theta bands) brain rhythms might be helpful in diagnosing cognitive dysfunction in PD. This delta/theta activity originates from areas of medial frontal cortex such as the anterior cingulate, and is detectable by mid-frontal scalp EEG electrodes. We have found that mid-frontal delta/theta brain rhythms are engaged when healthy individuals detect novelty, errors, and conflict, or make decisions. These rhythms are attenuated in PD patients. Our working model is that PD patients manifest diverse neuronal and network deficits that impair mid-frontal delta/theta activity, leading to failures in engaging cognitive control. These abnormalities contribute to PD-MCI and PDD. In this proposal we combine `big-data' machine learning tools, intraoperative neurophysiology in humans, and new brain-stimulation paradigms to investigate the role of mid-frontal delta/theta rhythms in PD. We will test the overall hypothesis that mid-frontal delta/theta impairments are a mechanism of cognitive dysfunction in PD. In Aim 1 we will determine if mid-frontal delta/theta activity predicts PD-MCI/PDD. In Aim 2 we will use unique intraoperative recordings to determine how delta/theta activity within medial frontal cortex influences neurons in the subthalamic nucleus, a key site of functional convergence that is targeted by current deep-brain stimulation for PD. Notably, the subthalamic nucleus is a compact structure that receives highly overlapping input from cognitive and motor cortical regions, making it likely that our recordings will capture cognitive processing within this nucleus. Finally, in Aim 3 we will determine if subthalamic nucleus deep-brain stimulation at delta/theta frequencies improves cognitive control in PD patients. Because these experiments involve recordings across several PD patient populations (Aim 1), from single subthalamic neurons (Aim 2), and brain stimulation (Aim 3), each of these aims will provide independent mechanistic insight into cognitive dysfunction in PD. PD is a complex disease, but if cortical EEG abnormalities are a consistent theme it might inspire new diagnostic tools or new brain-stimulation therapies for cognitive dysfunction in PD. Results from this proposal could also be important for other neurodegenerative diseases such as dementia with Lewy bodies and Alzheimer's disease.